Neha Priyadarshini Garg
Nanyang Technological University, Agency for Science, Technology and Research
Papers
7
Total Citations
71
H-Index
5
About
Neha Priyadarshini Garg is a robotics researcher whose work centers on human-robot interaction, shared autonomy, and assistive robotics. Her major contributions lie in developing learning-based systems that predict human intent to enable intuitive control of assistive devices. She pioneered motion-intention prediction for upper-limb assistive robots, allowing end-point control through natural onset movements, and applied Partially Observable Markov Decision Processes (POMDPs) to grasp objects under uncertainty—a critical capability for service robots. Garg also advanced shared control for robotic wheelchairs, creating intention-prediction systems that navigate point-to-point tasks while resolving user–robot conflicts. Her work on ExTraCT introduces explainable trajectory corrections using natural language, allowing robots to adapt motions based on user feedback without extensive retraining. With papers accumulating 18 citations each for her early works on motion-intention prediction and POMDP-based grasping, Garg’s research has clear impact in assistive robotics. Her 2023 shared autonomy paper on manipulator grasping under human intent uncertainty further demonstrates her ability to tackle real-world challenges. Garg’s innovative integration of learning, prediction, and explainability positions her as a rising leader in creating more responsive and trustworthy assistive robots.
Research Focus
Key Achievements
Top Papers
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- 2Learning To Grasp Under Uncertainty Using POMDPs18 citations · 2019
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